Built on top of a Geo-Distributed Analytics Server, ParStream CEO Peter Jensen says the querying engine based on a columnar database developed by ParStream has a footprint of only 50MB. That’s critical in IoT environments because it means the ParStream analytics platform can be deployed where data is being collected versus requiring organizations to continually transfer data back to a centralized data warehouse environment, says Jensen.

Compatible with SQL, organizations can then query the ParStream Analytics Server to access data that has been aggregated using the Vibe virtual data machine technology from Informatica. The result of those analytics can then be fed into data visualization tools from Datawatch.

Jensen says IoT applications require access to an analytics engine that is optimized for streaming data that often needs to be time-stamped. Designed from the ground up to support those applications, Jensen says that approach allows ParStream to correlate analytics based on both historical and real-time data to provide actionable insights.